Wireless communication using multiple-input multiple-output (MIMO) systems enables increased spectral efficiency for a given total transmit power. Increased capacity is achieved by introducing additional spatial channels in multipath dominant propagation environment, which are exploited by various techniques such as spatial multiplexing, space-time (Block) coding and others as a part of pre-processing to maximize isolations among these parallel channels. Many MIMO systems feature enhanced spectral efficiency for single users. A single use MIMO features a single multi-antenna transmitter communicating with a single multi-antenna receiver. Given a MIMO channel, duplex method and a transmission bandwidth, a system can be categorized according to (1) flat or frequency selective fading, and/or (2) with full, limited, or without transmitter channel state information (CSI).
In contrast, multi-user MIMO (MU-MIMO) is a set of advanced MIMO technologies where the available antenna elements are spread over a multitude of independent access points and independent radio terminals—each terminal with one or multiple elements. To enhance communication capabilities of all terminals, MU-MIMO applies an extended version of space-division multiple access (SDMA) to allow multiple transmitters to send separate signals and multiple receivers to receive separate signals simultaneously in the same frequency or time slots, or with same codes in the same frequency or time slots. There have been many MIMO-OFDM systems for multiple users' applications. Different users will use various sets of frequency slot distribution patterns over the same bandwidth over which orthogonal frequency components are radiated.
Our techniques exploit three aspects of propagation channels for multiple user MIMO systems; (1) the multiple parallel paths are through multiple active bent-pipe transponding platforms; (2) shaping MIMO channel transfer functions based on available channel state information (CSI) at transmission side including effects of propagating through multiple transponding platforms, and (3) applying WF multiplexing to efficiently sharing power and bandwidth provide by these transponding platforms among multiple users.
Transponding platforms include ground based basestations (BS), airborne platforms, and satellites. The airborne platforms may comprise of unmanned air vehicles (UAVs) equipped with transponders, which may be as large as in wing spans >100 ft carrying >10 medium or low power transponders operated above 10 Km in stratosphere, or as small as less than 6 inches carrying only one set of low power transponding devices usually operated at a height <1 km. Medium or low power transponders are referred to those with ˜10 Watt or ˜1 Watt radiated RF power, respectively. Transponding satellites may be configured as powerful as a high power communications satellite in geo-stationary earth orbit (GEO) with slightly less than 20 KW total DC power and >5000 Kg gross weight carrying >100 transponders with a height of ˜10 m with unfolded antennas and a width of ˜50 m measured with deployed solar panels. Some of transponding satellites may also be configured as small as a microsat carrying a low to medium power transponder in low earth orbits (LEO) with ˜10 W in total DC power, ˜1 Kg in gross weight, and a 10 cm cube in volume.
Present invention features additional pre-processing at transmission side on available channel state information (CSI) which is formulated via channel transfer functions/matrixes, simply composited transfer functions (CTFs), or composited transfer matrixes. The preprocessors are built via linear combinations of multiple transmitting antennas by beam forming networks, “shaping” the MIMO transfer functions. As a result, the inputs of the preprocessors become accessible to user-selectable composited transfer functions (CTFs), which are optimized via shaping and optimization algorithms; similar to many in smart beam shaping techniques. However, discrimination parameters for a composited transfer functions are not “constrained” in directions as those specified in conventional shaped beams. The constraints in the composited transfer functions are identified (ID) as “user indexed” or specified as “user ID indexed”. These user indexed performance constraints effectively enable optimizations for composited transfer functions so that frequency re-use via “directional diversity” become possible.
To make clear of meaning of a few technical terms related to multiple “active scattering platforms” in this application, we summarize a few below.                i. Active scattering platforms feature communications electronics which receive RF signals originated from a remote transmitter from a given direction through a receiving antenna. The received signals are amplified, filtered, “further processed”, and then power amplified before re-radiated toward various directions via a transmitting antenna. The pointing directions and coverage of the receiving and the transmitting antennas may not be the same. As a result, the incoming RF signals to these active scattering platforms are much weaker than the intensity levels of the re-radiated RF signals in various directions. The re-radiated RF signals may be “biased” to a preselected field of view (FOV).        ii. The FOV for the re-radiated RF signals may be remotely configurable        iii. The “further processed” may include frequency translations. In those cases the communications electronics on the active scattering platforms are transponders.        iv. When the transponding platforms are mobile airborne or space borne without de-modulations and re-modulations, their communications electronic payloads are non-regenerative transponders.        v. When users, including both transmitters and receivers remotely connected to the transponding platforms, are on ground or near ground, the non-regenerative electronic payloads are “bent-pipe” transponders.        vi. The transponding platforms may be dynamically distributed, ground base or near ground base, while remote users (either transmitting or receiving) are airborne or space borne. This feature shall be applicable of setting up a set of ground base crosslinks among low-earth-orbit (LEO) satellites via MIMO techniques.        vii. A p-to-p MIMO channel for enhanced channel capacity via frequency reused is built on the randomness of a dynamic distribution of the multiple platforms which feature a common coverage.        viii. For a p-to-mp scenario, each transponding platform will carry an aggregation of many sets of partial information to various receivers.        ix. A p-to-mp MIMO channel for multi-users via frequency re-usage is built on a randomness of a different dynamic distribution of the multiple platforms which feature concurrent but discriminative coverage. The discriminative resolution among multiple receivers relays on the dimensions of the distributed platforms.        
A composited transfer function (CTF) optimized under a finite number of user indexed performance constraints featuring a 1-to-m concurrent relationship, and is a spatially sampled radiation pattern of an optimally shaped beam viewed through a dynamic communication channel dominant by multiple paths. There are m spatially sampled outputs in a radiation pattern from an optimized BFN and only one common input to the BFN. In other words, this optimized function features integrated effects of an optimally shaped beam cascaded by effects of multiple scattering paths in a propagation channel. The function is optimized under the user indexed performance constraints via a selected optimization algorithm.
Composited transfer functions shaped for enhanced isolations among multiple users will have distinct responsive features to various users. For a two-user MIMO example in a multipath dominated environment; a first set of parallel preprocessors for transmission in a hub may feature composited transfer functions (CTFs), characterizing propagation paths from the inputs of the pre-processors all the way to various elements of the two user antennas, with “high” intensity responses to antenna elements of a first users while concurrently showing “low” intensity responses to a second users. Similarly, a second set of preprocessors may feature complex transfer functions (CTFs) with “low” intensity responses to all antenna elements of the first users while concurrently showing “high” intensity responses to those of the second users.
Outputs of two conventional MIMO processors, one for the first user and the other for the second user, are respectively connected to the inputs of the two sets of the preprocessors. The multiple outputs of the pre-processors are then connected to the same suite of the transmitting antenna elements. As a result, spectrum can be reused multiple times for better spectrum utility efficiency.
Our receiver design concepts include techniques incorporating multiple antenna elements and using space-time-frequency adaptive processing. Coordinated multi-user communication networks coordinate and/or combine signals from multiple antenna elements or base stations to make it possible for mobile users to enjoy consistent performance and quality when they access and share videos, photos and other high-bandwidth services, whether they are close to the center of their serving cell or at its outer edges. One issue with these networks is that conventional channel quality feedback schemes do not take into account a reduction in interference that can be achieved by coordination. Thus, there are general needs for these networks and methods for beamforming coordination that take into account the reduction in interference that results from the coordination of the base stations. There are also general needs for channel quality feedback schemes suitable for interference suppression in a coordinated multi-user network.